Search for: All records

While the COVID-19 pandemic morphs into less malignant forms, the virus has spawned a series of poorly understood, post-infection symptoms with staggering ramifications, i. e., long COVID (LC). This bibliometric study profiles the rapidly growing LC research domain [5,243 articles from PubMed and Web of Science (WoS)] to make its knowledge content more accessible. The article addresses What? Where? Who? and When? questions. A 13-topic Concept Grid presents bottom-up topic clusters. We break out those topics with other data fields, including disciplinary concentrations, topical details, and information on research “players” (countries, institutions, and authors) engaging in those topics. We provide access to results via a Dashboard website. We find a strongly growing, multidisciplinary LC research domain. That domain appears tightly connected based on shared research knowledge. However, we also observe notable concentrations of research activity in different disciplines. Data trends over 3 years of LC research suggest heightened attention to psychological and neurodegenerative symptoms, fatigue, and pulmonary involvement. 

Presentation showing the calculation of tech emergence indicators by state for nanotechnology research 

Technological convergence network (TCN) is an effective method to identify the advancement of technology convergence. However, the previous TCN investigations are limited to a single level of IPC (abbreviation of International Patent Classification) rather than different IPC hierarchies, which can only provide decision support for policy-makers with one dimension instead of various ones. In this study, we propose a new approach to construct TCNs across different IPC hierarchies based on technology co-classification analysis, and further identify key technology fields by employing the indicator of betweenness centrality (BC) in the TCNs from any IPC hierarchy. This study makes two important contributions. First, theoretically, our study is to contribute to understanding the advancement of technological convergence from various IPC hierarchies, rather than a single IPC level. Second, methodologically, the new approach we propose can benefit decision-makers serving at various levels of technology management agencies. We conclude possible implications and future directions. 

Abstract This article puts forth a new indicator of emerging technological topics as a tool for addressing challenges inherent in the evaluation of interdisciplinary research. We present this indicator and test its relationship with interdisciplinary and atypical research combinations. We perform this test by using metadata of scientific publications in three domains with different interdisciplinarity challenges: Nano-Enabled Drug Delivery, Synthetic Biology, and Autonomous Vehicles. Our analysis supports the connection between technological emergence and interdisciplinarity and atypicality in knowledge combinations. We further find that the contributions of interdisciplinary and atypical knowledge combinations to addressing emerging technological topics increase or stay constant over time. Implications for policymakers and contributions to the literature on interdisciplinarity and evaluation are provided.